Building on the Past: Enacting Established Personal Identities in a New Work Setting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A qualitative, longitudinal study of two groups of experienced professionals beginning work in a research organization provided insights into how newcomers with work experience adjust to and become assimilated into new jobs and work settings. Multiple methods were used to collect data on the newcomers' work experiences before and after assuming their new jobs. Repeated interviews with them during their first six months in their new jobs revealed that their past experience affected their assimilation in three primary ways: through the personal identities they had developed and carried with them, through the know-how they had acquired in past jobs and how well it fit with their new jobs, and through the personal tactics they had learned for managing their work and managing change. In general, newcomers with diverse experience adjusted better than those with narrow experience because (1) they found it easier to enact dimensions of their personal identities that allowed them to function effectively in the new situation, (2) they more easily found a fit between know-how gleaned from that experience and their new jobs, and (3) they could draw on a wider variety of personal tactics that they had previously used to help them adjust.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it